AC investment-committee
调用由查理·芒格、霍华德·马克斯、段永平、斯坦利·德鲁肯米勒、詹姆斯·西蒙斯组成的投资大师委员会，对任意标的进行多维度独立分析并输出委员会裁决报告。适用场景：(1) 买入判断——「委员会分析腾讯」「大师怎么看英伟达」「帮我分析BTC」；(2) 仓位管理——「我持有半仓BTC，怎么操作」「已持有NVDA，加仓还是减仓」；(3) 比较分析——「腾讯和谷歌选哪个」。支持股票（A/港/美）、ETF、BTC/加密资产、黄金/大宗商品。
As a process C 51/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions
How to improve
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
For the model run — optional
- Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
- A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.
Guard findings · 0
✓ No critical or high findings
Files scanned: 10. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
description-no-whendescription does not say WHEN to use the skill (no "use when")
Process rating: all ten parameters 51/100
- 0Result and completion. Does not say what the result is
- 0Inputs and preconditions. Does not say what the process needs to start
- 0Failures and branches. Linear process with no failure handling
- 0Progress reporting. Says nothing while it works
- 20When it triggers. No condition that starts the skill
- 30Running it twice. 2 mutating operations with no state check
- 100Tools and files. No external tools needed
- 100Steps. 12 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 465 tokens
Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.
Quality signals
- +5Description has no quoted example phrases that should trigger the skill
- +4Description does not say when NOT to use the skill (false activations)
- +3Output format is not stated: the model decides each time
- +1No license
- +2Single-language instructions
- +3Description length 214: enough signal without eating the budget
- +4Structure: 8 headings
- +3Step-by-step instructions: 12 items
- +4Has examples (3 code blocks)
- +4Reference files are cited in the instructions (6 of 6)
- +3All 1 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 79.
External checks
ClawHub: clean
This skill is a disclosed investment-analysis workflow that fetches market data, produces Chinese reports, and may post or save those reports, but it does not show hidden credential use, trading authority, or malicious behavior.
LLM: benign (high) · VirusTotal: · 29 May 2026